This invention relates to the non-invasive detection of abnormal blood flow sounds by an array of acoustic sensors.
The 20186 application describes an invention for the non-invasive in vivo detection and localization of abnormal blood flow. Embodiments of that invention entail display of the spatial distribution of phase coherence in the shear wave component blood flow signals generated by an acoustic sensor array. An essentially uniform display indicates normal blood flow. A non-uniform display may indicate the presence of an occlusion and the presence or extent of abnormal, turbulent blood flow. Poor correlation of signals from the array sensors may adversely affect the display uniformity.
Acoustic sensor arrays may be positioned above a measurement area defined as the (hairless) human chest skin located vertically between the sternum and a parallel line passing through the left nipple and horizontally 10 cm above and 6 cm below the left and right nipples.
A prior art acoustic sensor array comprising eight equally spaced sensors in two concentric circles having prime numbers of sensors in each circle and a ninth sensor at the common center of the concentric circles is illustrated by FIG. 6 of the 20186 application.
In operation, in order to reach sensors in a conventionally positioned prior art array as described in the 20186 application, sound waves must travel either directly through lung tissue or first to the body surface and then laterally with consequent attenuation of correlation. A study of the correlation by that array of patient data signals generated by the quiet interval has revealed that only four or five of the nine sensors are suitably or well correlated.
It is known that a notch (xe2x80x9ccardiac notchxe2x80x9d) in the human left lung allows the heart to be in contact with the chest wall. Well correlated blood flow signals may be generated by acoustic sensors positioned on a human chest in a small area (xe2x80x9cacoustic windowxe2x80x9d) located above the cardiac notch. The bounds of the acoustic window have been approximated by ultrasonic probe means as described in the xe2x80x9cSensor Arrayxe2x80x9d application.
However, there remains a need to be able to provide improved ways to identify the acoustic window for improved sensor operation and/or clinical applications.
The present invention employs a method for determining an acoustic window suitable for passive-acoustic coronary artery disease evaluation which includes the steps of (a) positioning a multi-channel acoustic sensor array (preferably having at least four and more preferably about 9-45 sensors) onto the chest of a subject; (b) calculating a weighted value for each of the sensor channels in the multi-channel sensor array; (c) determining the location of each sensor channel in the array; (d) identifying the sensor channels which meet predetermined test criteria; and (e) defining a perimeter which substantially extends about and encloses therewithin the sensor channels identified in step (d), thereby defining an acoustic window suitable for acoustic listening diagnostic procedures.
In a preferred embodiment the calculating step is performed by assigning signal to noise ratio (SNR) based weighted values to each of the sensor channels and the predetermined test criteria includes identifying the sensors exhibiting the three highest calculated weighted values or identifying at least three sensors exhibiting one or more high weight values. The acoustic window can be used to define one or more standard optimum sensor array geometry and sizes.
This invention involves the discovery that an acoustic window can be visualized by grayscale or equivalent mapping of optimal weights scaled to the estimated SNR on each of a plurality of channels of a multichannel acoustic sensor array to the nominal location of each sensor. The grayscale maps identify channels that achieve the highest SNR because the optimal weights represent a measure of the relative SNR distributed at each of the nominal sensor locations.
In operation, as shown in FIG. 7, the bounds of an acoustic window are visualized or defined by a perimeter (shown in dotted line) that encloses three or more channels that exhibit the highest relative SNR as measured by the optimal weights. The acoustic window is used to bound the aperture of an acoustic sensor array. This acoustic window identification increases or enhances the probability of acquiring the highest possible SNR on the largest percentage of sensors in the array.
Weightxe2x80x94For the purposes of this invention a xe2x80x9cweightxe2x80x9d is a constant applied to the SNR on single sensor channel as indicative of its relative importance among all involved channels. An algorithm for computing the weights, and preferably the optimal weights for each channel scaled to the estimated SNR thereon is described in the 20186 application, and herein at Appendix A. The algorithm operationally corresponds to and/or depends on having the same sensor location in all measurements for a particular person.
Sensor or Accelerometerxe2x80x94Any current or voltage mode device which generates an electric signal from displacement or a derivative thereof upon detection of a sound wave.
Sensor Arrayxe2x80x94A pattern or spaced arrangement of a plurality of sensors on or to be placed on the body surface of a patient. For the purposes of this invention an array comprises four or more sensors.
Sensor Array Aperturexe2x80x94The space or area within the perimeter of an array where heart or blood flow sounds are detected by a sensor(s) positioned therein.
Sensor Array Geometryxe2x80x94The shape of the perimeter of a sensor array.
Channelxe2x80x94The path followed by a signal from a sensor by which the signal is generated to a receiver. A sensor array includes multiple sensors and multiple channels.